tbuckley/cabot-search huggingface dataset:
Abstract 1548: CO-1008, an ADC program targeting leukemic progenitor and blast AML cells, but not normal hematopoetic progenitor cells
Authors: Garima Kaushik, Bandana Vishwakarma, Marina Bell, Kakajan Komurov
Journal: Cancer Research (2023)

Abstract The overall survival of patients diagnosed with Acute Myeloid Leukemia (AML) remains low. While initial responses to therapy are favorable, the duration of response is short, and overcoming therapeutic resistance has proven difficult. The presence of chemoresistant leukemic stem cells (LSCs), among other mechanisms, has been implicated as a driver in the observed relapse. Antibody-drug conjugates (ADC) are targeted cancer therapeutics that leverage antigen specificity to deliver a potent cytotoxic payload. Recently, ADCs have shown promise in the clinic, but can also present safety and efficacy concerns. Mylotarg, an FDA approved CD33-directed ADC used to treat Acute Myeloid Leukemia, was the first ADC to be approved. The therapeutic is active against most AML tumors but can lead to severe myelotoxicity given the expression of CD33 on normal myeloid progenitor cells. We leveraged a pharmaco-pheno-multiomic analysis of primary AML tumors to uncover a previously unexplored target expressed on both LSCs and AML blasts, but not normal hematopoetic progenitor cells or other normal tissue. The target also showed capacity to rapidly internalize and has activity of well-established oncogenic kinases associated with expression. A novel monoclonal antibody (IgG1) with favorable binding and biophysical characteristics was established against this novel target and conjugated to a highly potent cytotoxic agent, creating a novel ADC. This ADC shows strong binding across AML tumors with effective internalization and highly potent killing of AML tumors. Citation Format: Garima Kaushik, Bandana Vishwakarma, Marina Bell, Kakajan Komurov. CO-1008, an ADC program targeting leukemic progenitor and blast AML cells, but not normal hematopoetic progenitor cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1548.
Abstract 46: High-plex spatial transcriptomic characterization of canine tumor tissue
Authors: Sarah E. Church, Cheryl London, Christine M. Toedebusch, Ben Sutton, Sarah Weigel, Erin Piazza
Journal: Cancer Research (2023)

Abstract Background: Combination therapy to treat hematological and solid malignancies including chemotherapy, radiation, targeted and immunotherapy all hold huge potential for eliciting clinical responses. Informative pre-clinical testing of these approaches can be greatly facilitated using immune competent animals with spontaneous tumors. Pet dogs are immunologically outbred, immune competent and develop spontaneous tumors such as non Hodgkin’s lymphoma, glioblastoma, osteosarcoma, urothelial carcinoma and melanoma that share remarkable clinical, biological and genetic features with their human counterparts. As such, pre clinical testing of therapeutic approaches in dogs with cancer promises to accurately inform human clinical trial design. For this comparative approach to provide maximum information to accelerate human clinical translation of novel combination therapies and identify correlative biomarkers of therapeutic response, it is necessary to develop research tools for deep interrogation of the canine tumor microenvironment (TME). Here we present spatial transcriptomic analysis of multiple canine tumor and tissue types using GeoMx® digital spatial profiler (DSP) Canine Cancer Atlas (CCA) panel. Methods: FFPE slides or tissue microarrays were used to profile tumor and normal tissue from canines. Each slide was stained with tissue specific immunofluorescent antibodies, including Pan-cytokeratin, CD45, Vimentin, IBA1, CD3, and/or CD68. Regions of interest were selected to assess the TME and normal tissue as possible. Slides were then run on the DSP using the CCA panel that contains 1900-canine specific genes using standard DSP methods. Results: We were able to spatially detect over 1700 genes across multiple tissue types from canines, including osteosarcoma, glioblastoma, melanoma and normal tissues. Genes were detected in spatial compartments including malignant tumor, tumor stroma and normal tissue. Conclusions: Together the GeoMx CCA allow for interrogation of the TME of multiple tumor types and has the potential to inform spatial biomarkers for response to therapy, as well as translate the effectiveness of these therapies to humans. Citation Format: Sarah E. Church, Cheryl London, Christine M. Toedebusch, Ben Sutton, Sarah Weigel, Erin Piazza. High-plex spatial transcriptomic characterization of canine tumor tissue [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 46.
Abstract 5027: Targeting <i>ARAF</i> p.S214C mutation with sorafenib in non-small cell lung cancer
Authors: Carol Lee, Sze Man Chan, Sai Fung Yeung, Stephen Kwok-Wing Tsui
Journal: Cancer Research (2023)

Abstract Sorafenib is an FDA-approved multi-kinase inhibitor for the treatment of several cancer types, but is still under investigation for non-small cell lung cancer (NSCLC). Although sorafenib has not shown significant survival benefit in clinical trials for NSCLC patients, one study identified a patient with advanced lung adenocarcinoma harboring ARAF p.S214C mutation as an exceptional sorafenib responder. As NSCLC lacks clinically validated predictive biomarkers for drug responses, we aim to evaluate the potential of ARAF p.S214C mutation as a biomarker for sorafenib sensitivity and its mechanism of action. Constructs with ARAF p.S214C mutation, ARAF-wild type (WT) and EGFR-vector control were ectopically expressed in a lung adenocarcinoma cell line, H2023, by retroviral transduction. Western blot confirmed stable overexpression of ARAF proteins over time. MTT assay showed that sorafenib inhibited growth of cells expressing ARAF p.S214C more pronouncedly than cells expressing ARAF-WT or vector control. In addition, spheroids formed by cells expressing ARAF p.S214C were more sensitive to sorafenib inhibition, indicating sorafenib sensitivity of ARAF p.S214C in NSCLC in vitro. To evaluate whether such sorafenib sensitivity is dependent on the kinase activity of ARAF, phospho-MEK and MAPK levels in mutant cells will be determined. As ARAF belongs to the Raf protein family which also includes BRAF and RAF1, knockdown studies and co-immunoprecipitation will be performed to determine whether BRAF and RAF1 are essential for ARAF p.S214C activity. The in vivo sorafenib sensitivity of ARAF p.S214C will be validated in tumor xenografts established from cells expressing the above constructs upon sorafenib treatment. Tumor volume will be assessed and expression of the tumor marker cytokeratin will be evaluated by immunohistochemistry. This study may reveal ARAF p.S214C as a potential biomarker for sorafenib sensitivity and a new target for precision medicine in NSCLC. Citation Format: Carol Lee, Sze Man Chan, Sai Fung Yeung, Stephen Kwok-Wing Tsui. Targeting ARAF p.S214C mutation with sorafenib in non-small cell lung cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5027.
Abstract 4292: Gene model correction for PVRIG and TIGIT in single cell sequencing data enables accurate detection and study of its functional relevance
Authors: Sergey Nemzer, Niv Sabath, Assaf Wool, Zoya Altber, Hirofumi Ando, Drew M. Pardoll, Sudipto Ganguly, Yaron Turpaz, Zurit Levine, Roy Z. Granit
Journal: Cancer Research (2023)

Abstract Single cell RNA sequencing (scRNA-seq) has gained increased popularity in recent years and has revolutionized the study of cell populations; however, this technology presents several caveats regarding specific gene expression measurement. Here we examine the expression levels of several immune checkpoint genes, which are currently assessed in clinical studies. We find that unlike in most bulk sequencing studies, PVRIG and murine TIGIT suffers from poor detection in 10x Chromium scRNA-seq and other types of assays that utilize the GENCODE gene model. We show that the default GENCODE gene model, typically used in the analysis of such data, is incorrect in the PVRIG genomic region and contains also a predicted read-through transcript to which PVRIG reads co-align, causing these to be discarded and hence hindering its proper detection. Moreover, we find that the murine TIGIT 3’ UTR is mis-annotated, leading to the loss of legitimate reads. We thus generated a corrected reference genome, by removing the faulty read-through in the case of PVRIG and by extending the TIGIT 3’ UTR and demonstrate that by employing these changes we can correctly capture genuine expression levels of these checkpoints, and which align with our findings at the protein level using FACS and CITEseq. Furthermore, we show that specialized read multimap algorithms such as RSEM and STARsolo can also partially improve the detection of PVRIG. Our study provides means to better interrogate the expression of PVRIG and murine TIGIT in scRNA-seq and emphasize the importance of optimizing gene models and alignment algorithms to enable accurate gene expression measurement in scRNA-seq and bulk sequencing. Moreover, our results support detailed study of the expression of immune checkpoints in clinical and pre-clinical studies towards the development of cancer immunotherapy treatments. Citation Format: Sergey Nemzer, Niv Sabath, Assaf Wool, Zoya Altber, Hirofumi Ando, Drew M. Pardoll, Sudipto Ganguly, Yaron Turpaz, Zurit Levine, Roy Z. Granit. Gene model correction for PVRIG and TIGIT in single cell sequencing data enables accurate detection and study of its functional relevance. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4292.
Abstract 5408: AI powered-platform to predict gene modifications from prostate and breast cancer whole slide images
Authors: Wei Huang, Parag Jain, Chensu Xie, Hassan Muhammad, Hirak Basu, George Wilding, Rajat Roy
Journal: Cancer Research (2023)

Abstract There is little published evidence of predicting cancer genotypes directly from tissue histology, especially for breast and prostate cancers. Artificial intelligence (AI) enables discriminating and extracting morphological features reflective of the underlying genomic alterations at visual and subvisual levels. We have built a morphology-based and AI-powered platform for cancer genotyping, risk stratification and outcome prediction that addresses the needs for treatment decision-making in a cost effective and timely fashion. A cohort of 390 prostate and 742 invasive breast cancer patients with known molecular status of key genes, such as TP53, PIK3CA, MYC, ERBB2, TMPRSS2-ERG and PTEN from The Cancer Genome Atlas were included in this study. Hematoxylin and eosin (H&amp;E) stained whole slide images (WSI) of the cancer tissue sections were available at 20x or 40x. The WSI from the two cancer cohorts were split 2:1 into a training and test dataset, respectively. Our platform involved two different deep Convolutional Neural Network (DCNN) architectures. The platform first divided each WSI into multiple tiles. Each tile was then analyzed using a DCNN that graded the tile and generated a high dimensional vector to provide a mathematical representation of the morphology. The combination of high dimensional vectors across the WSI was then fed into a second DCNN that generated a morphological score, which predicted whether the gene under consideration was wild type or modified. Our platform has achieved 70 - 80% accuracy as defined by the Area under the Curve for the receiver operating characteristics curves for the genetic markers on the test cohorts (Table 1). Our platform can predict genotypes/molecular alterations directly from H&amp;E stained WSI with high accuracy. This technology presents a novel, practical and cost-effective approach for cancer molecular classification and risk stratification, enabling timely and optimal treatment decision-making for positive clinical outcomes. Genotype Prediction for Breast Cancer (BrCa) and Prostate Cancer (PCa) from WSI Cohort Molecular Biomarker Training Dataset (n) Test Dataset (n) Test ROC AUC Score (%) Gene Modification/Loss Intact/Wild type Gene Modification/Loss Intact/Wild type BrCa TP53 196 302 96 149 80 PIK3CA 153 344 75 170 74 MYC 68 414 33 204 77 ERBB2 66 416 32 205 78 PCa TMPRSS2-ERG 104 157 51 78 70 PTEN 57 201 28 99 73 Citation Format: Wei Huang, Parag Jain, Chensu Xie, Hassan Muhammad, Hirak Basu, George Wilding, Rajat Roy. AI powered-platform to predict gene modifications from prostate and breast cancer whole slide images. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5408.
Abstract 447: Genetic and pharmacological inhibition of TUT4 and TUT7 sensitizes AML cells to BCL-2 inhibition
Authors: Corey Fyfe, Gabriella Fiorentino, Michael J. Steinbaugh, Joana Campos, Hannah Lawson, Jozef Durko, Donal O'Carroll, Kamil Kranc, Darren Harvey, Shomir Ghosh, Robert M. Campbell
Journal: Cancer Research (2023)

Abstract The terminal uridyltransferases TUT4/7 (ZCCHC11/6) are important mediators of RNA stability, RNA decay, histone mRNA regulation, viral RNA sensing, and miRNA biogenesis. Regulation of RNA processing pathways can be mediated by a number of RNA-binding proteins (RBPs), and dysfunctional RNA processing has implications as a therapeutic target in leukemia and lymphoma. We performed genetic and pharmacological perturbation of the activity of terminal uridyltransferases TUT4/7 (ZCCHC11/6) in MLL-rearranged acute myeloid leukemia (AML). A combination of catalytic inactivation and knockout by CRISPR/Cas9 of TUT4 and TUT7, respectively, were used to abrogate uridylation in THP-1 cells, with enzyme function measured by a cellular miRNA uridylation assay. Inhibition of uridylation in THP-1 cells reduced proliferation, induced changes in cell cycle progression, and enhanced sensitivity to the BCL-2 inhibitor, venetoclax, alone and in combination with azacitidine. BCL-2 expression was found to be reduced at the mRNA and protein levels, while increases in expression of BCL-2 regulating miRNAs miR139-5p and miR494-3p were observed. GSEA performed on uridylation deficient cells highlighted changes in cell cycle regulation, mitochondrial metabolism, and cell death pathways relative to unedited controls. These effects could be recapitulated with pharmacological inhibition using sub-inhibitory doses of a novel, selective inhibitor of TUT4/7, TS-002266, while the weakly active enantiomer TS-002455 did not show combination activity. Treatment of primary AML with combination of TS-002266 and venetoclax improved activity over venetoclax alone in a number of primary AML samples. Thus, we propose that TUT4/7 and BCL-2 inactivation may be a therapeutic strategy in leukemia. Citation Format: Corey Fyfe, Gabriella Fiorentino, Michael J. Steinbaugh, Joana Campos, Hannah Lawson, Jozef Durko, Donal O'Carroll, Kamil Kranc, Darren Harvey, Shomir Ghosh, Robert M. Campbell. Genetic and pharmacological inhibition of TUT4 and TUT7 sensitizes AML cells to BCL-2 inhibition [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 447.
Abstract 3899: CHST11 mediated SEMA7A expression contributes to TKI resistant in lung cancer
Authors: Chien-Hsiu Chris Li, Ming-Hsien Chan, Yu-Chan Chang, Michael Hsiao
Journal: Cancer Research (2023)

Abstract An extracellular matrix has been demonstrated to be one of the substances that promote tumor cells to become driven by external stimuli to change their biology or malignancy. The main component of extracellular matrix, chondroitin sulfate, has been confirmed as a factor in the progression of tumors. Nevertheless, a great deal remains unknown regarding the precise mechanisms that drive Chondroitin sulfate production and how these details are communicated to cancer cells. According to our previous studies, the main enzyme responsible for Chondroitin sulfate synthesis, carbohydrate sulfotransferase 11 (CHST11), plays a crucial role in lung cancer cell metastatic spread. Nevertheless, the relationship between CHST11 expression and regulatory mechanism in response to lung cancer treatment is unclear, especially for tyrosine kinase inhibitor (TKI). A clinical correlation analysis was used in this study to identify molecules which were highly correlated with the overexpression of CHST11 and identified GPI-anchored protein semaphorin 7A (SEMA7A) as a candidate. According to the TCGA database, expression of upregulated SEMA7A is correlated with poor prognosis and cellular malignancy in lung cancer patients. A SEMA7A-based gene correlation analysis finds that the affected gene ontology is highly similar to CHST11, particularly integrin signaling, which may contribute to Gefitinib resistance. A GSEA analysis reveals a significant effect of CHST11 overexpression on mitotic spindle processes, some of which molecules are clinically relevant to CHST11 or SEMA7A. These molecules have been reported to be involved in TKI resistance events such as MARCKS, MYO1E, and PDLIM5. Based on the TCGA database, these molecules and integrins also display significant clinical relevance in lung cancer patients. A CHST11-mediated increase in SEMA7A in the mitotic spindle process of cells may serve as one of the possible means of reducing TKI-induced mitotic cell death, and thereby promoting the ability of lung cancer cells to become resistant to TKIs. Hence, targeting the CHST11-SEMA7A axis may offer a therapeutic strategy option that could be used to target drug resistance in lung cancers. [Keywords: CHST11, SEMA7A, Integrin, Drug resistant, Lung cancer] (Reference: https://pubmed.ncbi.nlm.nih.gov/35985204/; https://pubmed.ncbi.nlm.nih.gov/36181245/) Citation Format: Chien-Hsiu Chris Li, Ming-Hsien Chan, Yu-Chan Chang, Michael Hsiao. CHST11 mediated SEMA7A expression contributes to TKI resistant in lung cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3899.
Abstract 4865: Mechanisms of EGFR inhibitor sensitivity and resistance in chordoma
Authors: Nindo Punturi, Lee Dolat, Joan Levy, Josh Sommer, Daniel M. Freed
Journal: Cancer Research (2023)

Abstract Target discovery studies have identified EGFR inhibition as a promising therapeutic strategy in chordoma, motivating ongoing clinical trials. Yet EGFR is not mutated in chordoma, leaving the mechanisms associated with EGFR inhibitor (EGFRi) sensitivity and resistance unclear. In this study, we profiled a panel of over 10 chordoma cell lines to categorize their sensitivity to afatinib, a second-generation EGFRi with potency against the wild-type receptor. Several cell lines, including U-CHCF365, UM-Chor1, MUG-Chor1, and U-CH1, were highly sensitive to afatinib in cell viability assays, with absolute IC50 values below 50 nanomolar. In contrast, other chordoma cell lines, including UM-Chor5C and U-CHCF359B, exhibited limited response to EGFRi at concentrations exceeding 1 micromolar. Among sensitive cell lines, we found that afatinib promoted cell death in some cases (e.g., U-CH1) whereas in others it induced a profound cell cycle arrest. Moreover, in U-CH1 cells, acute afatinib treatment enriched a population of drug-tolerant persister cells with a fusiform morphology, potentially indicative of an epithelial-mesenchymal transition. Ongoing studies are focused on understanding the mechanisms of afatinib-induced cell death, drug tolerance, and acquired resistance, with a view to designing rational combination strategies capable of enhancing the magnitude and duration of therapeutic response. In cell lines with matched xenograft models, in vitro responses to afatinib were consistent in vivo. In a panel of 12 chordoma patient-derived xenograft (PDX) models treated with afatinib or cetuximab, differential sensitivity to EGFRi was recapitulated - with EGFRi promoting complete or negligent tumor growth inhibition in sensitive or resistant models, respectively. Finally, we combined drug sensitivity profiling of chordoma cell lines and PDXs with whole-exome and whole-transcriptome sequencing to identify genomic and transcriptomic features associated with sensitivity and resistance to EGFRi in chordoma. Collectively, our data identify a striking degree of differential sensitivity to EGFRi in chordoma, and begin to shed light on factors associated with primary and acquired resistance. These results provide a framework for guiding patient selection and identifying potential combination therapy regimens to improve EGFRi efficacy and address resistance. Citation Format: Nindo Punturi, Lee Dolat, Joan Levy, Josh Sommer, Daniel M. Freed. Mechanisms of EGFR inhibitor sensitivity and resistance in chordoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4865.